Optical coherence tomography imaging biomarkers associated with neovascular age-related macular degeneration: a systematic review

Eye (Lond). 2023 Aug;37(12):2438-2453. doi: 10.1038/s41433-022-02360-4. Epub 2022 Dec 16.

Abstract

The aim of this systematic literature review is twofold, (1) detail the impact of retinal biomarkers identifiable via optical coherence tomography (OCT) on disease progression and response to treatment in neovascular age-related macular degeneration (nAMD) and (2) establish which biomarkers are currently identifiable by artificial intelligence (AI) models and the utilisation of this technology. Following the PRISMA guidelines, PubMed was searched for peer-reviewed publications dated between January 2016 and January 2022.

Population: Patients diagnosed with nAMD with OCT imaging.

Settings: Comparable settings to NHS hospitals.

Study designs: Randomised controlled trials, prospective/retrospective cohort studies and review articles. From 228 articles, 130 were full-text reviewed, 50 were removed for falling outside the scope of this review with 10 added from the author's inventory, resulting in the inclusion of 90 articles. From 9 biomarkers identified; intraretinal fluid (IRF), subretinal fluid, pigment epithelial detachment, subretinal hyperreflective material (SHRM), retinal pigmental epithelial (RPE) atrophy, drusen, outer retinal tabulation (ORT), hyperreflective foci (HF) and retinal thickness, 5 are considered pertinent to nAMD disease progression; IRF, SHRM, drusen, ORT and HF. A number of these biomarkers can be classified using current AI models. Significant retinal biomarkers pertinent to disease activity and progression in nAMD are identifiable via OCT; IRF being the most important in terms of the significant impact on visual outcome. Incorporating AI into ophthalmology practice is a promising advancement towards automated and reproducible analyses of OCT data with the ability to diagnose disease and predict future disease conversion.

Systematic review registration: This review has been registered with PROSPERO (registration ID: CRD42021233200).

摘要: 本综述有两个主要目的:1) 详细说明通过相干光断层扫描 (OCT) 可识别的视网膜生物标志物对新生血管性老年黄斑变性 (nAMD) 疾病进展和治疗反应的影响;2) 确定目前哪些生物标志物可由人工智能 (AI) 模型识别,以及该技术的应用情况.本文遵循PRISMA指南,在2016年1月至2022年1月期间使用PubMed数据库对同行评审出版物进行了系统检索.人群:经OCT成像诊断为nAMD的患者.设置:与NHS医院相似的环境.研究设计:随机对照试验、前瞻性/回顾性队列研究和综述文章. 在228篇文献中,对130篇进行了全文查阅,50篇因不属于本综述的范围而被删除,加入10篇来自作者清单的文章,最后纳入90篇.在确定的9个生物标志物中:视网膜内液 (IRF) 、视网膜下液、色素上皮脱落、视网膜下高反射物质 (SHRM) 、视网膜色素上皮 (RPE) 萎缩、玻璃膜疣、外层视网膜管状结构 (ORT) 、高反射灶 (HF) 和视网膜厚度中,有5个被认为与nAMD疾病进展有关:IRF、SHRM、黄斑、ORT和HF.部分生物标志物可以用目前的人工智能模型进行分类.与nAMD疾病活动和进展相关的重要视网膜生物标志物可通过OCT识别;IRF对视力结果的影响最为显著.将人工智能纳入眼科实践是OCT数据自动化和可重现分析的一个具有前景的进步,其拥有诊断和预测疾病转换的能力.

Publication types

  • Systematic Review
  • Review

MeSH terms

  • Angiogenesis Inhibitors / therapeutic use
  • Artificial Intelligence
  • Biomarkers
  • Disease Progression
  • Fluorescein Angiography
  • Humans
  • Macular Degeneration* / drug therapy
  • Prospective Studies
  • Retrospective Studies
  • Tomography, Optical Coherence / methods
  • Wet Macular Degeneration* / complications
  • Wet Macular Degeneration* / diagnosis

Substances

  • Biomarkers
  • Angiogenesis Inhibitors